/*
 *    This program is free software; you can redistribute it and/or modify
 *    it under the terms of the GNU General Public License as published by
 *    the Free Software Foundation; either version 2 of the License, or
 *    (at your option) any later version.
 *
 *    This program is distributed in the hope that it will be useful,
 *    but WITHOUT ANY WARRANTY; without even the implied warranty of
 *    MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
 *    GNU General Public License for more details.
 *
 *    You should have received a copy of the GNU General Public License
 *    along with this program; if not, write to the Free Software
 *    Foundation, Inc., 675 Mass Ave, Cambridge, MA 02139, USA.
 */

/*
 *    TwoWayNumericSplit.java
 *    Copyright (C) 2001 University of Waikato, Hamilton, New Zealand
 *
 */

package weka.classifiers.trees.adtree;

import weka.core.Instance;
import weka.core.Instances;
import weka.core.RevisionUtils;
import weka.core.Utils;

import java.util.Enumeration;

/**
 * Class representing a two-way split on a numeric attribute, of the form:
 * either 'is < some_value' or 'is >= some_value'.
 *
 * @author Richard Kirkby (rkirkby@cs.waikato.ac.nz)
 * @version $Revision: 1.6 $
 */
public class TwoWayNumericSplit
  extends Splitter {

  /** for serialization */
  private static final long serialVersionUID = 449769177903158283L;

  /** The index of the attribute the split depends on */
  private int attIndex;

  /** The attribute value that is compared against */
  private double splitPoint;

  /** The children of this split */
  private PredictionNode[] children;

  /**
   * Creates a new two-way numeric splitter.
   *
   * @param _attIndex the index of the attribute this split depeneds on
   * @param _splitPoint the attribute value that the splitter splits on
   */
  public TwoWayNumericSplit(int _attIndex, double _splitPoint) {

    attIndex = _attIndex;
    splitPoint = _splitPoint;
    children = new PredictionNode[2];
  }
  
  /**
   * Gets the number of branches of the split.
   *
   * @return the number of branches (always = 2)
   */
  public int getNumOfBranches() { 
    
    return 2;
  }

  /**
   * Gets the index of the branch that an instance applies to. Returns -1 if no branches
   * apply.
   *
   * @param inst the instance
   * @return the branch index
   */
  public int branchInstanceGoesDown(Instance inst) {
    
    if (inst.isMissing(attIndex)) return -1;
    else if (inst.value(attIndex) < splitPoint) return 0;
    else return 1;
  }

  /**
   * Gets the subset of instances that apply to a particluar branch of the split. If the
   * branch index is -1, the subset will consist of those instances that don't apply to
   * any branch.
   *
   * @param branch the index of the branch
   * @param instances the instances from which to find the subset 
   * @return the set of instances that apply
   */
  public ReferenceInstances instancesDownBranch(int branch, Instances instances) {
    
    ReferenceInstances filteredInstances = new ReferenceInstances(instances, 1);
    if (branch == -1) {
      for (Enumeration e = instances.enumerateInstances(); e.hasMoreElements(); ) {
	Instance inst = (Instance) e.nextElement();
	if (inst.isMissing(attIndex)) filteredInstances.addReference(inst);
      }
    } else if (branch == 0) {
      for (Enumeration e = instances.enumerateInstances(); e.hasMoreElements(); ) {
	Instance inst = (Instance) e.nextElement();
	if (!inst.isMissing(attIndex) && inst.value(attIndex) < splitPoint)
	  filteredInstances.addReference(inst);
      }
    } else {
      for (Enumeration e = instances.enumerateInstances(); e.hasMoreElements(); ) {
	Instance inst = (Instance) e.nextElement();
	if (!inst.isMissing(attIndex) && inst.value(attIndex) >= splitPoint)
	  filteredInstances.addReference(inst);
      }
    }
    return filteredInstances;
  }
  
  /**
   * Gets the string describing the attributes the split depends on.
   * i.e. the left hand side of the description of the split.
   *
   * @param dataset the dataset that the split is based on
   * @return a string describing the attributes
   */  
  public String attributeString(Instances dataset) {
  
    return dataset.attribute(attIndex).name();
  }

  /**
   * Gets the string describing the comparision the split depends on for a particular
   * branch. i.e. the right hand side of the description of the split.
   *
   * @param branchNum the branch of the split
   * @param dataset the dataset that the split is based on
   * @return a string describing the comparison
   */
  public String comparisonString(int branchNum, Instances dataset) {
    
    return ((branchNum == 0 ? "< " : ">= ") + Utils.doubleToString(splitPoint, 3));
  }

  /**
   * Tests whether two splitters are equivalent.
   *
   * @param compare the splitter to compare with
   * @return whether or not they match
   */
  public boolean equalTo(Splitter compare) {
    
    if (compare instanceof TwoWayNumericSplit) { // test object type
      TwoWayNumericSplit compareSame = (TwoWayNumericSplit) compare;
      return (attIndex == compareSame.attIndex &&
	      splitPoint == compareSame.splitPoint);
    } else return false;
  }

  /**
   * Sets the child for a branch of the split.
   *
   * @param branchNum the branch to set the child for
   * @param childPredictor the new child
   */
  public void setChildForBranch(int branchNum, PredictionNode childPredictor) {
    
    children[branchNum] = childPredictor;
  }

  /**
   * Gets the child for a branch of the split.
   *
   * @param branchNum the branch to get the child for
   * @return the child
   */
  public PredictionNode getChildForBranch(int branchNum) {
    
    return children[branchNum];
  }

  /**
   * Clones this node. Performs a deep copy, recursing through the tree.
   *
   * @return a clone
   */
  public Object clone() {
    
    TwoWayNumericSplit clone = new TwoWayNumericSplit(attIndex, splitPoint);
    clone.orderAdded = orderAdded;
    if (children[0] != null)
      clone.setChildForBranch(0, (PredictionNode) children[0].clone());
    if (children[1] != null)
      clone.setChildForBranch(1, (PredictionNode) children[1].clone());
    return clone;
  }
  
  /**
   * Returns the revision string.
   * 
   * @return		the revision
   */
  public String getRevision() {
    return RevisionUtils.extract("$Revision: 1.6 $");
  }
}
